Systems and methods for implementing a multi-sensor receiver in a DSM3 environment

ABSTRACT

In accordance with one embodiment, a method is implemented in a vectored system for improving a signal-to-noise ratio (SNR) of a far end transmitted signal on a victim line in the system. The method comprises mitigating, by the vectored system, self-induced far-end crosstalk (self-FEXT) on the victim line based on self-FEXT mitigation coefficients and receiving, by a second sensor, information relating to at least one of: self-FEXT of the vectored system, external noise, and the far end transmitted signal. The method further comprises learning, at the second sensor, coefficients relating to self-FEXT coupling into the second sensor and removing self-FEXT from the second sensor based on the learned coefficients. Upon removal of self-FEXT from the second sensor, a linear combiner configured to combine information relating to the victim line and the second line is learned. The method further comprises applying the learned linear combiner and readjusting the self-FEXT mitigation coefficients to remove any residual self-FEXT on the victim line after application of the learned linear combiner.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims priority to, and the benefit of, U.S.Provisional patent application entitled, “Dual Sensor Xtalk Canceller ina DSM3 Environment,” having Ser. No. 61/316,606, filed on Mar. 23, 2010,which is incorporated by reference in its entirety.

TECHNICAL FIELD

The present disclosure generally relates to digital subscriber linesystems and particularly, to implementation of dual sensor crosstalkcancellation.

BACKGROUND

Digital subscriber line (xDSL) technology has developed in recent yearsin response to the demand for high-speed Internet access. xDSLtechnology utilizes the communication medium of pre-existing telephonesystems. Thus, both plain old telephone systems (POTS) and xDSL systemsshare a common line for xDSL-compatible customer premises. Similarly,other services such as time compression multiplexing (TCM) integratedservices digital network (ISDN) can also share a common line with xDSLand POTS.

Allocations of wire pairs within telephone cables in accordance withservice requests have typically resulted in a random distribution ofpair utilization with few precise records of actual configurations.Because of the physical proximity of bundled cables (due to pairtwisting, cable branching, cable splicing, etc.), crosstalk caused bythe electromagnetic interference between the neighboring lines is oftenthe dominating noise source in the transmission environment. Inaddition, due to pair twisting in cables where cable branching andsplicing take place, a wire pair can be in close proximity to manydifferent pairs spanning different portions of its length. At atelephone CO (central office), pairs in close proximity may carrydiverse types of service using various modulation schemes, withconsiderable differences in signal levels (and receiver sensitivities)especially for pairs of considerably different lengths.

There are generally two types of crosstalk mechanisms that arecharacterized, one being FEXT and the other one being near-end crosstalk(NEXT). FEXT refers to electromagnetic coupling that occurs when thereceiver on a disturbed pair is located at the far end of thecommunication line as the transmitter of a disturbing pair. Self inducedfar end crosstalk (self-FEXT) generally refers to interference caused byneighboring lines provisioned for the same type of service as theaffected line, or “victim line.” In contrast, NEXT results from adisturbing source connected at one end of the wire pair which causesinterference in the message channel at the same end as the disturbingsource. Current approaches to addressing crosstalk suffer from variousperceived shortcomings. While vectored systems are effective inaddressing such disturbances as self-FEXT, various types ofinterferences such as radio frequency interference (RFI), power linecommunications (PLC), common mode noise, and impulse nose remain anissue.

SUMMARY

Various embodiments are described. One embodiment is a methodimplemented in a vectored system for improving a signal-to-noise ratio(SNR) of a far end transmitted signal on a victim line in the system.The method comprises mitigating, by the vectored system, self-inducedfar-end crosstalk (self-FEXT) on the victim line based on self-FEXTmitigation coefficients and receiving, by a second sensor, informationrelating to at least one of: self-FEXT of the vectored system, externalnoise, and the far end transmitted signal. The method further compriseslearning, at the second sensor, coefficients relating to self-FEXTcoupling into the second sensor and removing self-FEXT from the secondsensor based on the learned coefficients. Upon removal of self-FEXT fromthe second sensor, a linear combiner configured to combine informationrelating to the victim line and the second line is learned. The methodfurther comprises applying the learned linear combiner and readjustingthe self-FEXT mitigation coefficients to remove any residual self-FEXTon the victim line after application of the learned linear combiner.

In accordance with another embodiment, a method for improving asignal-to-noise ratio (SNR) of a far end transmitted signal on a victimline in a system, comprises receiving, by the victim line, at least oneof: self-induced far-end crosstalk (self-FEXT) of the vectored system,external noise, and the far end transmitted signal and receiving, by asecond sensor, at least one of: self-FEXT of the vectored system,external noise, and the far end transmitted signal. The method furthercomprises learning, at the victim line, coefficients relating toself-FEXT coupling into the main line, wherein learning is performedbased on known training mode sequences transmitted in the system andlearning, at the second sensor, coefficients relating to self-FEXTcoupling into the second sensor, wherein learning is performed based onknown training mode sequences transmitted in the system. The methodfurther comprises removing, at the victim line, self-FEXT from the mainline based on the learned coefficients and removing, at the secondsensor, self-FEXT from the second sensor based on the learnedcoefficients. A linear combiner is learned upon removing self-FEXT fromboth the main line and the second sensor, the linear combiner configuredto combine information relating to the victim line and the secondsensor. The method further comprises applying the learned linearcombiner and learning the self FEXT mitigation coefficients andperforming noise mitigation on the victim line to remove self-FEXT onthe victim line.

Another embodiment is a vectored system configured to improve asignal-to-noise ratio (SNR) of a far end transmitted signal on a victimline, comprising a far end crosstalk (FEXT) mitigator configured tomitigate self-induced far-end crosstalk (self-FEXT) on the victim linebased on self-FEXT mitigation coefficients, a first sensor coupled tothe victim line, and a second sensor, the second sensor configured toreceive information relating to at least to one of: the vectored system,external noise, and the far end transmitted signal on the victim line.The second sensor is further configured to learn coefficients relatingto self-FEXT coupling into the second sensor and remove self-FEXT basedon the learned coefficients. The system further comprises a linearcombiner configured to undergo learning upon removal of self-FEXT fromthe second sensor, wherein the linear combiner is configured to combineinformation relating to the victim line and the second line, wherein theFEXT mitigator is further configured to readjust the self-FEXTmitigation coefficients to remove any residual self-FEXT on the victimline after application of the learned linear combiner.

Another embodiment is a method implemented in customer premisesequipment (CPE) for improving a signal-to-noise ratio (SNR) of a far endtransmitted signal on a victim line. The method comprises receiving, bythe victim line, one or more of: the far end transmitted signal,self-induced far-end crosstalk (self-FEXT) of a vectored system, andexternal noise. The method further comprises receiving, by a secondsensor, one or more of: the far end transmitted signal, self-inducedfar-end crosstalk (self-FEXT) of a vectored system, and external noise.Based on the presence of self-FEXT, coefficients relating to self-FEXTcoupling into the victim line at learned at the victim line. The methodfurther comprises learning, at the second sensor, coefficients relatingto self-FEXT coupling into the second sensor. Responsive to the presenceof self-FEXT, self-FEXT is removed from the victim line based on thelearned coefficients. Self-FEXT is removed from the second sensor basedon the learned coefficients. Upon removal of self-FEXT from the secondsensor, a linear combiner configured to combine information relating tothe victim line and the second line is learned. The method furthercomprise applying the learned linear combiner.

Another embodiment is a customer premises equipment (CPE) unit in avectored system for improving a signal-to-noise ratio (SNR) of a far endtransmitted signal on a victim line. The CPE comprises a first sensorcoupled to the victim line, the first sensor configured to learncoefficients relating to self-induced far-end crosstalk (self-FEXT)coupling into the first sensor and remove self-FEXT based on the learnedcoefficients. The CPE further comprises a second sensor configured toreceive information relating to at least one of: the vectored system,external noise, and the far end transmitted signal on the victim line,the second sensor further configured to learn coefficients relating toself-FEXT coupling into the second sensor and remove self-FEXT based onthe learned coefficients. The CPE further comprises a linear combinerconfigured to undergo learning upon removal of self-FEXT from the firstand the second sensor, wherein the linear combiner is configured tocombine information relating to the victim line and the second line.

Other systems, methods, features, and advantages of the presentdisclosure will be or become apparent to one with skill in the art uponexamination of the following drawings and detailed description. It isintended that all such additional systems, methods, features, andadvantages be included within this description, be within the scope ofthe present disclosure, and be protected by the accompanying claims.

BRIEF DESCRIPTION OF THE DRAWINGS

Many aspects of the disclosure can be better understood with referenceto the following drawings. The components in the drawings are notnecessarily to scale, emphasis instead being placed upon clearlyillustrating the principles of the present disclosure. Moreover, in thedrawings, like reference numerals designate corresponding partsthroughout the several views.

FIG. 1 depicts a communication system in which embodiments of a dualsensor configuration are implemented.

FIG. 2 is an embodiment of the CPE shown in the system of FIG. 1.

FIG. 3 is an embodiment of the receiver shown in FIG. 2.

FIG. 4A depicts an embodiment of the second sensor comprising adifferential mode sensor coupled to another line in the same bundle asthe victim line.

FIG. 4B depicts an alternative embodiment of the second sensorcomprising a common sensor coupled between the victim line comprising atwisted pair and ground.

FIG. 5 is a flowchart in accordance with one embodiment for mitigatingalien noise or combining diverse received information using a dualsensor configuration.

FIG. 6 is a flowchart in accordance with another embodiment formitigating alien noise or combining diverse received information using adual sensor configuration.

FIG. 7 is a flowchart in accordance with another embodiment formitigating alien noise or combining diverse received information using adual sensor configuration.

DETAILED DESCRIPTION

Having summarized various aspects of the present disclosure, referencewill now be made in detail to the description of the disclosure asillustrated in the drawings. While the disclosure will be described inconnection with these drawings, there is no intent to limit it to theembodiment or embodiments disclosed herein. On the contrary, the intentis to cover all alternatives, modifications and equivalents includedwithin the spirit and scope of the disclosure as defined by the appendedclaims.

Various embodiments are disclosed related to the use of a second sensorat the receiver in a vectoring environment, where the receiver is eitherimplemented at the central office (CO) or at the customer premisesequipment (CPE). In accordance with some embodiments, a second sensor isused with a noise canceller when the information captured by the secondsensor relates to noise. The second sensor may also be used in thecontext of a diversity receiver when the information carried by thesecond sensor is related to useful transmit information. It should befurther emphasized that the second sensor may also be used when theinformation received by the sensor relates to an external noise and auseful signal. Embodiments of a dual sensor receiver are described withrespect to an alien noise canceller located at the customer premisesequipment (CPE) for the downstream data path. Note, however, that theconcepts described can be extended to a diversity receiver or any othertype of joint receiver configuration based on a second sensor. Theconcepts can also be extended to the upstream path where the receiver islocated on the CO side. Finally, it should also be noted that theconcepts relating to one sensor and one victim line can also be extendedto apply to multiple victim lines and multiple sensors used by a samereceiver. In this regard, variations and modifications may be made tothe embodiments described herein without departing from the principlesof the present disclosure.

In very high speed digital subscriber line (VDSL) systems, crosstalk isgenerally a large concern. While near end crosstalk (NEXT) tends to benegligible by construction, self induced far-end crosstalk (self-FEXT)is typically the dominant large band noise in VDSL systems.Nevertheless, self-FEXT has been addressed by introducing vectoringsolutions across bundles. Reference is made to FIG. 1, which illustratesa communication system in a vectoring environment. One vectoring method,for example, relates to reducing self-induced far end crosstalk(self-FEXT) in a multiple input multiple output (MIMO) digitalsubscriber line (xDSL) system.

As VDSL2 systems generally share a same twisted pair cable bundle,self-FEXT noise can be mitigated. For the upstream direction, self-FEXTmitigation is performed through a per tone joint canceller at thecentral office (CO) in the frequency domain before or after thefrequency equalizer (FEQ). Additional details regarding self-FEXT noisemitigation techniques can be found in U.S. Pat. No. 7,835,368, filed onMay 20, 2008, entitled “System and Method for Mitigating the Effects ofUpstream Far-End Cross-Talk,” which is herein incorporated by referencein its entirety. For self-FEXT cancellation in the downstream path, theuse of a joint canceller is not relevant as the customer premisesequipment (CPE) are not co-located. As a result, a precoding approach isusually chosen, which means that the self-FEXT noise is cancelled at thetransmitter via pre-compensation. Additional details regarding MIMOprecoding in an xDSL system are described in U.S. application Ser. No.11/845,040, filed on Aug. 25, 2007, entitled “Systems and Methods forMIMO Precoding in an xDSL System,” which is also herein incorporated byreference in its entirety. For purposes of this disclosure, self-FEXTmitigation generally refers to vectoring self-FEXT noise cancellationtechniques in a vectored system.

While vectored systems are effective in addressing such disturbances asself-FEXT, various types of interferences such as non-vectored VDSL2FEXT, radio frequency interference (RFI), power line communications(PLC), common mode noise, and impulse noise remain an issue as vectoringis not effective in mitigating these disturbers. Such disturbers aregenerally located in the frequency spectrum, and communication systemsgenerally experience one or two of these disturbers. When the twistedpairs share the same cable bundle, the vectoring system does not alwaysreach optimal performance (as optimized to account for background noise)as external noise can also affect the system.

To cancel or compensate this type of noise, a per tone dual sensorreceiver (DSR) may be used in conjunction with information received by asecond sensor, where the DSR operates in the frequency domain to addressalien disturbers. As noted earlier, the concepts relating to one sensorcan also be extended to apply to multiple sensors used by a samereceiver. It is possible to have a main, victim path and a second pathboth affected by the same noise synchronously. This second sensor canbe, for example, a differential mode twisted pair unused line in thesame bundle as the victim line or a common mode sensor. To furtherillustrate, reference is made to FIGS. 4A and 4B. FIG. 4A depicts adifferential mode sensor coupled to another line in the same bundle asthe victim line. FIG. 4B depicts a common sensor coupled between thetwisted pair comprising the victim line and ground. Additional detailsregarding the use of a common mode signal to obtain additionalinformation that can be used to better approximate the transmittedsignal are disclosed in U.S. Pat. No. 6,999,504, filed Mar. 15, 2001,entitled “System and Method for Canceling Crosstalk,” hereinincorporated by reference in its entirety. One limitation with the dualsensor receiver described above is that the presence of more than one ortwo disturbers becomes an issue as signals begin to exhibit attributessimilar to white noise, which results in reduced diversity at thereceiver. This ultimately results in reduced performance. As the noiseis usually located in a specific frequency spectrum, a frequencyapproach (or per tone after a FFT operator) is usually suggested.

The CPE 110 in FIG. 1 includes a FEXT mitigator 106 and a receiver 204,where the receiver 204 is configured to receive data from thetransceivers 140 a at the CO 130 under the self-FEXT disturbance of 140b, c. Reference is made to FIG. 3, which provides a detailed view of thereceiver 204 in FIG. 1. The frequency approach described hereingenerally requires that the information received by a second sensor(e.g., common mode sensor) be processed in a suitable manner than themainstream information, up to the output of the fast Fourier transform(FFT) operator. In that order, the synchronization of the data flow isconserved, and thus the correlation of the signal on the two streams isgenerally maintained. In some specific cases, as in the case of adiversity receiver, the time domain signals need to be desynchronized inorder to maximize the signal-to-noise ratio (SNR).

As shown in FIG. 3, the receiver 204 comprises various modules. Filters302 a, 302 b (e.g., analog and digital) are applied to the receivesignal in order to increase the dynamic range of the receive signal inthe useful frequency band. As the channel can introduce a large amountof Inter Symbol Interference (ISI), the receiver 204 further comprises atime equalizer (TEQ) 304 a configured to shorten the channel impulseresponse to a cyclic extension length. The TEQ 304 a is learned andapplied to the downstream direct path. This TEQ 304 a is then reproducedon the process path of the second sensor (TEQ 304 b). After removing thecyclic extension on both received signals using the cyclic extensionmodules 306 a, 306 b, an FFT operation is performed by the FFT blocks308 a, 308 b, and the received signal is forwarded to a dual sensorreceiver (DSR) 310 and on to a decoder 312.

FIG. 2 depicts an embodiment of the CPE 110 in FIG. 1. In addition to areceiver 204 and a second sensor 206, the CPE 110 may also include aprocessor 202, a memory component 212 which may include volatile and/ornonvolatile memory components, and data storage 228 such as mass memorythat are communicatively coupled via a local interface 210. The localinterface 210 may include other elements such as controllers, buffers(caches), drivers, repeaters, and receivers to enable communications.Further, the local interface 210 may include address, control, and/ordata connections to enable appropriate communications among theaforementioned components 202, 212, 228.

The processor 202 in the CPE 110 is configured to execute softwarestored on a tangible storage medium such as the memory component 212.The processor 202 can be any custom made or commercially availableprocessor, a central processing unit (CPU), an auxiliary processor amongseveral processors, a semiconductor based microprocessor (in the form ofa microchip or chip set), a macroprocessor, or generally any device forexecuting software instructions. The memory component 212 can includeany one or combination of volatile memory elements (e.g., random accessmemory (RAM, such as DRAM, SRAM, SDRAM, etc.)) and/or nonvolatile memoryelements (e.g., ROM, hard drive, tape, CDROM, etc.). Moreover, thememory component 212 may incorporate electronic, magnetic, optical,and/or other types of storage media. One should note that someembodiments of the memory component 212 can have a distributedarchitecture (where various components are situated remotely from oneanother), but can be accessed by the processor 202.

Software stored on the memory component 212 may include one or moreseparate programs, each of which includes an ordered listing ofexecutable instructions for implementing logical functions. For example,the software in the memory component may include an operating system214. Furthermore, the software residing in memory may includeapplication specific software 216 configured to perform some or all ofthe functions associated with the dual sensor system described herein.It should be noted that these modules can be implemented in software,hardware or a combination of software and hardware. When implemented insoftware, the modules are stored on a non-transitory computer readablemedium and executed by the processor 202. The operating system 214 maybe configured to control the execution of other computer programs andprovides scheduling, input-output control, file and data management,memory management, and communication control and related services.

A system component and/or module embodied as software may also beconstrued as a source program, executable program (object code), script,or any other entity comprising a set of instructions to be performed.When constructed as a source program, the program is translated via acompiler, assembler, interpreter, or the like, which may or may not beincluded within the memory component, so as to operate properly inconnection with the operating system.

Let the signal received by a typical VDSL2 receiver on the main, victimline be represented by:Y _(m) [q,t]=H _(m) [q]×[q,t]+S _(m) +W _(m) [q,t],where the signal is in frequency domain per tone q for DMT symbol tafter undergoing a fast Fourier transform (FFT) operation in thefrequency domain. The term H represents the direct channel; X is thetransmitted information; S represents self-FEXT noise from the vectoredsystem; and W represents external noise such as background noise,impulse noise, PLC, and so on.

As all the lines in a vectored system are synchronized, the self-FEXTdisturber can be readily identified, and in that matter, othertechniques can also be used to identify the self-FEXT channel. In thisregard, VDSL2 systems with vectoring engaged typically provide aself-FEXT free environment via self-FEXT mitigation In a given bundle,for example, the effects of self-FEXT can be mitigated through theprecoding of data for downstream transmission to cancel self-FEXT, whilein the upstream direction, joint cancellation may be deployed. Thesignal received on the victim line after vectoring is turned on isrepresented as follows:Y _(m) [q,t]=H _(m) [q]×[q,t]+W _(m) [q,t],where Y represents the signal in the frequency domain after undergoingan FFT operation.

When external noise sources (e.g., alien noise disturbers) such asnon-vectored VDSL2 FEXT, radio frequency interference (RFI), power linecommunications (PLC), common mode noise, and impulse noise remain, thedual sensor receiver (DSR) may be used in conjunction with a secondsensor information operating in the frequency domain to address aliendisturbers as described below. In the context of the alien noisecanceller, the signal received by the second sensor in the frequencydomain per tone q for a DMT symbol t after undergoing an FFT operationis represented by the following:Y _(s) [q,t]=S _(s) +W _(s) [q,t]

The second sensor acts as a noise alone reference (NAR). The secondsensor (whether a common mode sensor or a differential mode sensor) iseffective in capturing information relating to the noise source. In thefrequency domain, a linear combination of information relating to thereceiver on the two paths (corresponding to the victim line and thesecond sensor) can then be used to reduce or compensate for the aliendisturber, thereby improving performance. With an alien noise canceller,the signal-to-noise ratio (SNR) is maximized and the noise in thefrequency domain is compensated for using a per tone algorithm.Specifically, this is performed using a per tone linear combineroptimally learned according to such criteria as minimum mean squareerror, zero forcing, maximum likelihood (ML), or other type of criteria.In such cases, the output information is represented as:{tilde over (X)}[q,t]=F _(m) Y _(m) [q,t]+F _(s) Y _(s) [q,t],where Y represents the received signal, and F represents the linearcombiner coefficients. Note that the linear combiner is not limited totwo coefficients (F) as the linear combiner can also use only onecoefficient F per tone q, even on the receive signal of the victim lineor the second sensor.

One limitation with the dual sensor receiver described above is that thepresence of more than one or two disturbers destroys the correlationbetween the received signals, and which results in reduced diversity atthe receiver. In the current vectoring system scenario, the secondsensor is not free of self-FEXT by construction. Thus, one issue withutilizing a second sensor here is that the second sensor will not onlyexperience such disturbances as RFI and PCL but also the effects ofself-FEXT which have not been compensated for by the precoder and whichcould be the most powerful received signal, thereby diminishing theproperties of a noise alone reference (NAR). This leads to poorperformance, and in general, no noise cancellation.

Various embodiments are thus described for utilizing a DSR inconjunction with a second sensor whereby self-FEXT on the second sensoris removed so that the information can be effectively utilized duringthe per tone linear combiner training. It is possible to locally removethe component related to the self-FEXT on the second sensor for specificreceived sequences in training mode and in data mode on DMT symbolsreferred to as sync symbols. In fact, sync symbols are known trainingDMT symbols that occur in data mode every 257 symbols and during which,by using an orthogonal key such as a Hadamard sequence, for example,every user of the vectoring system has a signature. In that specificcontext, it is possible to estimate at the receiver the contributionfrom the self-FEXT of every transmitter and as a consequence, mitigatethe self-FEXT. This technique serves as the basis of the vectoringsystem as mentioned earlier. Note that on top of the sync symbol,decision-directed techniques (using data mode symbols) for estimatingthe self-FEXT mitigation coefficients can also be used when all thereceivers are co-located, which is typically the case at the CO. In thatcontext and based on local knowledge at the CPE of each key sequence ofthe vectoring system (for example, known by default by the CPE ortransmitted by the CO in proprietary fields), the receiver can removethe contribution of the self-FEXT from the second sensor:{tilde over (Y)} _(s) [q,t]=Y _(s) [q,t]−{tilde over (S)} _(s) =W _(s)[q,t],where {tilde over (S)} is the estimate of the self-FEXT in the secondsensor. The last component is then used as the true external noise alonereference and the linear combiner can be optimized for noisecancellation training. Under those conditions, a true FEXT-freeenvironment is achieved as the main victim line is FEXT free due to itspresence in a vectored system:Y _(m) [q,t]=H _(m) [q]×[q,t]+W _(m) [q,t]

Once the second sensor is free of self-FEXT, the noise cancellerundergoes a learning process in order to optimize the noise canceller tomitigate the one or more alien disturbers. Upon completion of thelearning process by the noise canceller, the removal of self-FEXT fromthe second sensor receive path is stopped. Specifically, when the linearcombiner coefficient F has been learned, the received signal during datamode is represented by the following:{tilde over (X)}[q,t]=F _(m) Y _(m) [q,t]+F _(s) Y _(s) [q,t]=X[q,t]+F_(s) S _(s) [q,t]+{tilde over (W)}.The self-FEXT experienced by the second sensor is thus folded into themain, victim line. This folded self-FEXT now present on the victim lineis mitigated according to the same self-FEXT mitigation operator usedearlier to mitigate self-FEXT on the main, victim line.

The receive signal from the noise canceller thus experiences self-FEXTas the vectored system only compensates for self-FEXT originally sensedon the main line. In this regard, self-FEXT from the second sensor isnow “folded” into the main line. This folded self-FEXT on the main lineis then readily removed or compensated for in the vectored system bysimply readjusting the self-FEXT canceller (e.g., precoder or upstreamcanceller) and utilizing the error estimated after the use of the aliennoise canceller. Note that while embodiments herein are described in thecontext of the customer premises equipment (CPE), the embodiments can beexpanded and implemented at the central office (CO) as well.

It should be emphasized that the technique described above can also beexpanded to diversity receivers, which utilize more than onecommunication channel with different channel characteristics to receiveinformation related to the transmitted signal on the victim line, whichwill be referred to herein as transmit information or usefulinformation. In fact in VDSL systems, the transmit information sent overa twisted pair generally leaks through other channels such as, forexample, an adjacent twisted pair of the same bundle through the FEXTchannel or in common mode. It is also possible to transmit informationon the common mode channel of the differential mode line under certainpower constraints. In both cases, the far end transmit information canbe received on a second sensor, and the folding of this usefulinformation from the second sensor into the main line can be leveragedwith a linear combiner and thus increase the SNR of the system. In adiversity receiver embodiment utilizing a second sensor, the far endtransmitted signal received by the second sensor in the frequency domainfor tone q for a DMT symbol t after undergoing an FFT operation isrepresented by the following:Y _(m) [q,t]=H _(m) [q]×[q,t]+S _(s) +W _(m) [q,t].As a vectoring system is being used, the second sensor is also subjectto self-FEXT. Because the self-FEXT component can be powerful, thelinear combiner used at the receiver in the frequency domain cannot betrained as the training will be biased by the self-FEXT. As with theother embodiments described earlier in the context of an alien noisecanceller, self-FEXT can be first removed from the second sensor at thereceiver after learning locally the self-FEXT canceller during knownsymbols with the knowledge of the orthogonal key. The combiner thenundergoes a learning phase in an optimal manner as it is no longerbiased by the self-FEXT from the second sensor. Thus, for a diversityreceiver embodiment, the linear combiner coefficient F is learned in aself-FEXT free environment:Y _(m) [q,t]=H _(m) [q]×[q,t]+W _(m) [q,t]{tilde over (Y)} _(s) [q,t]=Y _(s) [q,t]−{tilde over (S)} _(s) =H _(s)[q]×[q,t]+W _(s) [q,t]The component {tilde over (S)} is once again estimated as it isestimated in a vectoring system locally during the transmission of syncsymbols or any other orthogonal training sequence. After the coefficientF has been learned, the received signal during data mode is:{tilde over (X)}[q,t]=F _(m) Y _(m) [q,t]+F _(s) Y _(s) [q,t]=X[q,t]+F_(s) S _(s) [q,t]+{tilde over (W)},where the self-FEXT from the second sensor is again folded into themain, victim line. This folded self-FEXT is then mitigated using thesame mitigation operator used for the main line (e.g., vectoringdownstream precoder or an upstream canceller). When the linear combineris applied, the self-FEXT is folded into the main line from the secondsensor. The vectored system then adapts to the folded self-FEXT suchthat the folded self-FEXT is removed or compensated for on the mainline.

By implementing the various dual sensor configurations described herein,the DSR 310 (in FIG. 3) is able to reduce any residual external noiseresulting from such sources as radio frequency interference (RFI) andpower line communications (PLC) after the removal of self-FEXT. Themixed combination of the information received on the second sensorrelated to external noise and useful information need to also be takeninto consideration. In that scenario, the DSR can be trained to minimizethe impact of the noise while simultaneously maximizing the folding ofthe useful signal/information.

In accordance with an embodiment for the alien noise mitigation and thediversity receiver based on a dual sensor configuration, a methodimplemented in a communication system for reducing noise experienced andSNR gain by a victim line is now described in connection with FIG. 5.Although the flowchart 500 of FIG. 5 shows a specific order ofexecution, it is understood that the order of execution may differ fromthat which is depicted. In block 510 the vectoring system runs itsalgorithms in order to eliminate any self-FEXT contribution from themain victim line. The introduction of the second sensor, carryinginformation about a residual external noise and/or the usefulinformation is made. Self-FEXT noise also appears on the second sensorand may affect the performance of the DSR receiver. In block 520, theself-FEXT coupling coefficients of the second sensor are learned duringknown symbols based on the knowledge of the transmitted information onthe disturber lines (i.e., known symbol) and the orthogonal sequences.Other techniques could also be used to estimate the self-FEXT couplings.

After a learning phase, in block 530, the estimated self-FEXT on eachknown symbol is removed from the second sensor received signal. In block540, the linear combiner is learned in a self-FEXT free environment.After the learning phase of the linear combiner, the linear combiner isapplied (block 550) during data mode symbol and self-FEXT from thesecond sensor is folded into the main victim. In order to compensate forthis residual component of self-FEXT, the vectoring algorithm isreadjusted in block 560.

It should be emphasized that the re-adjustment of the self-FEXTmitigation coefficients in block 560 is predictable as the folded noiseis directly related to the self-FEXT canceller coefficients used toremove the self-FEXT from the second sensor during the known symbol andthe linear combiner coefficients. Thus, a fast update of the self-FEXTmitigation coefficients based on those previous primitives (e.g., linearcombiner coefficients, self-FEXT mitigation coefficients) can beachieved. For self-FEXT mitigation in the downstream direction, theuseful information can also be transmitted to the CO through proprietaryfields. Finally, note that the linear combiner learned in a self-FEXTfree environment utilizes the useful information received on the secondsensor when no external noise is present (as in a diversity receiverscenario).

The embodiment described in connection with the flowchart 500 of FIG. 5relates to a vectored system. The stages outlined can be all performedlocally at the receiver (e.g., an upstream receiver located at the COside). In the context of the downstream channel, the vectored self-FEXTmitigation task will be performed at the CO side via, for example, aprecoder technique. The local mitigation of the self-FEXT on the secondsensor and the learning of the linear combiner as well as application ofthe linear combiner will be performed at the CPE receiver.

If embodied in software, each block depicted in FIG. 5 represents amodule, segment, or portion of code that comprises program instructionsstored on a non-transitory computer readable medium to implement thespecified logical function(s). In this regard, the program instructionsmay be embodied in the form of source code that comprises statementswritten in a programming language or machine code that comprisesnumerical instructions recognizable by a suitable execution system suchas a processor in a computer system or other system such as the CPE 110shown in FIG. 2. The machine code may be converted from the source code,etc. If embodied in hardware, each block may represent a circuit or anumber of interconnected circuits to implement the specified logicalfunction(s). The technique leverages the fact that exact knowledge ofFEXT coupling can generally be used to improve performance andpredictability of the performance gain. Precise identification of thecrosstalk channel on both the main line and second sensor line can bederived by means of cross-correlation of aligned orthogonal sequencesassigned to downstream known symbol sequences, as with dynamic spectrummanagement level 3 (DSM3). Note that the use of a perfectly orthogonalset of known symbol sequences allows one to determine and regularlyupdate self-FEXT mitigation coefficients to cancel the identifieddominant (or non-dominant) crosstalk source in a manner similar to anupstream DSM3 crosstalk canceller. This addresses the imperfectcorrelation problem identified for other dual sensor approaches.

In accordance with alternative embodiments, DSR training may occur priorto DSM3 self-FEXT noise mitigation. Reference is made to FIG. 6.Although the flowchart 600 of FIG. 6 shows a specific order ofexecution, it is understood that the order of execution may differ fromthat which is depicted. In a non-DSM3 environment, self-FEXT disturberchannel coefficients are estimated locally at the CPE 110 c using aknown orthogonal sequence of known symbols (block 610) for the mainvictim line. In block 620, the self-FEXT disturber is removed from thevictim line on known symbols using known orthogonal sequences and theestimated channel coefficients. In block 630, the self-FEXT disturberchannel coefficients relating to the second sensor are estimated at thereceiver, using a known orthogonal sequence of known symbols. Theself-FEXT contribution is thus removed from the second sensor (block640). In block 650, the training of the linear combiner is completedduring the known symbol period as the transmit disturber information isknown by the receiver. In block 660, the linear combiner is applied toremove common correlated noise on data symbols or to fold constructivelyuseful information into the main line, and thereby folding any self-FEXTresidual noise into the victim line. In block 670, DSM3 coefficients aredetermined to reduce the folded self-FEXT as well as the originalself-FEXT experienced by the victim line.

It again should be emphasized that the learning of the self-FEXTmitigation coefficients is predictable as the folded noise is directlyrelated to the self-FEXT canceller coefficients used to remove theself-FEXT from the second sensor during the known symbol and the linearcombiner coefficients. Thus, a fast update of the self-FEXT mitigationcoefficients based on those previous primitives (e.g., linear combinercoefficients, self-FEXT mitigation coefficients) can be achieved. Forself-FEXT mitigation in the downstream direction, the useful informationcan also be transmitted to the CO through proprietary fields. Finally,note that the linear combiner learned in a self-FEXT free environmentutilizes the useful information received on the second sensor when noexternal noise is present (as in a diversity receiver scenario).

In accordance with other embodiments, DSR training may be performed toreduce the impact of an external disturber, which is greater than theself-FEXT experienced by the main, victim line but less powerful thanthe self-FEXT experienced by the second sensor. For such scenarios, aDSM3 noise mitigation module is not required. Reference is made to FIG.7. Although the flowchart 700 of FIG. 7 shows a specific order ofexecution, it is understood that the order of execution may differ fromthat which is depicted. Self-FEXT disturber channel coefficients areestimated locally at the CPE 110 c using the known orthogonal sequenceduring known symbols (block 710) for the main victim line and the secondsensor (block 710). The self-FEXT disturber is removed from the victimline and the second sensor on known symbols, and the linear combiner istrained in this self-FEXT free environment (block 720). The linearcombiner is then applied to remove common correlated noise on datasymbols or to fold constructively useful information into the main line(block 730) and thereby adding into the main, victim line any self-FEXTresidual noise from the second sensor. Note that this is useful in itscurrent form only if the effect of the folded self-FEXT from the secondsensor is still less than the current canceled external noise. Once theexternal noise is cancelled, the performance of the victim line islimited by self-FEXT noise, which may be mitigated using vectoringtechniques. Note also that the linear combiner learned during theself-FEXT free environment utilizes the useful information received onthe second sensor when no external noise is present (as in a diversityreceiver scenario).

The embodiment described in connection with FIG. 7 can be extended tothe case where the DSR is used without any self-FEXT mitigationtechnique being applied and with no external noise present. In suchcases, a first group composed of the most dominant self-FEXT disturber(or a set of the most dominant self-FEXT disturbers) can be consideredequivalent to external noise (such as the external noise describedearlier) and thus be mitigated with an alien noise canceller. During thetraining period of the linear combiner on known symbols, the receiverestimates and then removes the second group of self-FEXT composed of thenon-dominant self-FEXT noise from the main line and the second sensor.After the compensation phase, the linear combiner can be learned suchthat the linear combiner only mitigates the first group of dominantself-FEXT disturbances. After the learning phase, the linear combiner isapplied to the data symbol, and performance is driven by the folding ofthe (unmitigated) second group of self-FEXT into the main victim line.

It should be emphasized that the above-described embodiments are merelyexamples of possible implementations. Many variations and modificationsmay be made to the above-described embodiments without departing fromthe principles of the present disclosure. All such modifications andvariations are intended to be included herein within the scope of thisdisclosure and protected by the following claims.

At least the following is claimed:
 1. A method implemented in a vectoredsystem for improving a signal-to-noise ratio (SNR) of a far endtransmitted signal on a victim line in the system, comprising:mitigating, by the vectored system, self-induced far-end crosstalk(self-FEXT) on the victim line based on self-FEXT mitigationcoefficients; receiving, by a second sensor, information relating to anoise source comprising at least one of: self-FEXT of the vectoredsystem, external noise, and the far end transmitted signal, wherein thesecond sensor is configured to receive the information relating to thenoise source exclusive of any useful signals in the system; learning, atthe second sensor, coefficients relating to self-FEXT coupling into thesecond sensor; removing self-FEXT from the second sensor based on thelearned coefficients; upon removal of self-FEXT from the second sensor,learning a linear combiner configured to combine information relating tothe victim line and the noise source; applying the learned linearcombiner; and readjusting the self-FEXT mitigation coefficients toremove any residual self-FEXT on the victim line after application ofthe learned linear combiner.
 2. The method of claim 1, wherein learninga linear combiner is performed according to one of the followingcriteria: minimum mean square error, zero forcing, and maximumlikelihood (ML).
 3. The method of claim 1, wherein learning coefficientsrelating to self-FEXT coupling into the second sensor is performedaccording to a known sequence transmitted on one or more disturber linescausing the self-FEXT into the victim line.
 4. The method of claim 3,wherein learning coefficients relating to self-FEXT coupling into thesecond sensor is further performed using one or more orthogonalsequences.
 5. The method of claim 1, wherein learning coefficientsrelating to self-FEXT coupling into the second sensor is performedduring transmission of data mode symbols.
 6. The method of claim 1,wherein receiving information relating to the vectored system comprisesreceiving information relating to external noise composed of at leastone of: non-vectored very high-speed digital subscriber line (VDSL)FEXT, radio frequency interference (RFI), power line communications(PLC), common mode noise, and impulse noise.
 7. The method of claim 1,wherein applying the learned linear combiner comprises mitigatingexternal noise if the information received by the second sensor relatesto the external noise.
 8. The method of claim 1, wherein applying thelearned linear combiner comprises constructively folding the far endtransmitted signal from the second sensor into the victim line if theinformation received by the second sensor relates to the far endtransmitted signal.
 9. The method of claim 1, wherein applying thelearned linear combiner comprises constructively folding the far endtransmitted signal from the second sensor into the victim line andmitigating external noise if the information received by the secondsensor relates to both the far end transmitted signal and the externalnoise.
 10. The method of claim 1, wherein the linear combiner operatesaccording to one or two coefficients per tone.
 11. The method of claim1, wherein readjusting the self-FEXT mitigation coefficients isperformed based on previously-learned self-FEXT mitigation coefficientsor another initial state of the self-FEXT mitigation coefficients.
 12. Amethod for improving a signal-to-noise ratio (SNR) of a far endtransmitted signal on a victim line in a system, comprising: receiving,by the victim line, at least one of: self-induced far-end crosstalk(self-FEXT) of the vectored system, external noise, and the far endtransmitted signal; receiving, by a second sensor, a noise signalcomprising at least one of: self-FEXT of the vectored system, externalnoise, and the far end transmitted signal, wherein the second sensor isconfigured to receive the noise signal exclusive of any useful signalsin the system; learning, at the victim line, coefficients relating toself-FEXT coupling into the victim line, wherein learning is performedbased on known training mode sequences transmitted in the system;learning, at the second sensor, coefficients relating to self-FEXTcoupling into the second sensor, wherein learning is performed based onknown training mode sequences transmitted in the system; removing, atthe victim line, self-FEXT from the main line based on the learnedcoefficients; removing, at the second sensor, self-FEXT from the secondsensor based on the learned coefficients; learning a linear combinerupon removing self-FEXT from both the main line and the second sensor,the linear combiner configured to combine information relating to thevictim line and the second sensor; applying the learned linear combiner;and learning the self FEXT mitigation coefficients and performing noisemitigation on the victim line to remove self-FEXT on the victim line.13. A vectored system configured to improve a signal-to-noise ratio(SNR) of a far end transmitted signal on a victim line, comprising: afar end crosstalk (FEXT) mitigator configured to mitigate self-inducedfar-end crosstalk (self-FEXT) on the victim line based on self-FEXTmitigation coefficients; a first sensor coupled to the victim line; asecond sensor, the second sensor configured to receive informationrelating to a noise source comprising at least to one of: the vectoredsystem, external noise, and the far end transmitted signal on the victimline, wherein the second sensor is configured to receive the informationrelating to the noise source exclusive of any useful signals in thesystem; the second sensor further configured to learn coefficientsrelating to self-FEXT coupling into the second sensor and removeself-FEXT based on the learned coefficients; and a linear combinerconfigured to undergo learning upon removal of self-FEXT from the secondsensor, wherein the linear combiner is configured to combine informationrelating to the victim line and the noise source; wherein the FEXTmitigator is further configured to readjust the self-FEXT mitigationcoefficients to remove any residual self-FEXT on the victim line afterapplication of the learned linear combiner.
 14. The system of claim 13,wherein the second sensor is configured to operate according to adifferential mode involving another twisted pair in the system or acommon mode based on the victim line.
 15. The system of claim 13,wherein learning a linear combiner is performed according to one of thefollowing criteria: minimum mean square error, zero forcing, and maximumlikelihood (ML).
 16. The system of claim 13, wherein informationrelating external noise comprises one or more of: non-vectored veryhigh-speed digital subscriber line (VDSL) FEXT, radio frequencyinterference (RFI), power line communications (PLC), common mode noise,and impulse noise.
 17. The system of claim 13, wherein the learnedlinear combiner mitigates external noise if the information received bythe second sensor relates to the external noise.
 18. The system of claim13, wherein the learned linear combiner constructively folds the far endtransmitted signal from the second sensor into the victim line if theinformation received by the second sensor relates to the far endtransmitted signal.
 19. The system of claim 13, wherein the learnedlinear combiner constructively folds the far end transmitted signal fromthe second sensor into the victim line and mitigates external noise ifthe information received by the second sensor relates to both the farend transmitted signal and the external noise.
 20. The system of claim13, wherein the linear combiner operates according to one or twocoefficients per tone.
 21. The system of claim 13, wherein the FEXTmitigator readjusts the self-FEXT mitigation coefficients based onpreviously-learned self-FEXT mitigation coefficients or an initial stateof the self-FEXT mitigation coefficients.
 22. A method implemented incustomer premises equipment (CPE) for improving a signal-to-noise ratio(SNR) of a far end transmitted signal on a victim line, comprising:receiving, by the victim line, one or more of: the far end transmittedsignal, self-induced far-end crosstalk (self-FEXT) of a vectored system,and external noise; receiving, by a second sensor, information relatingto a noise source comprising one or more of: the far end transmittedsignal, self-induced far-end crosstalk (self-FEXT) of a vectored system,and external noise, wherein the second sensor is configured to receivethe information relating to the noise source exclusive of any usefulsignals in the system; based on the presence of self-FEXT, learning, atthe victim line, coefficients relating to self-FEXT coupling into thevictim line; learning, at the second sensor, coefficients relating toself-FEXT coupling into the second sensor; responsive to the presence ofself-FEXT, removing self-FEXT from the victim line based on the learnedcoefficients; removing self-FEXT from the second sensor based on thelearned coefficients; upon removal of self-FEXT from the second sensor,learning a linear combiner configured to combine information relating tothe victim line and the noise source; and applying the learned linearcombiner.
 23. The method of claim 22, wherein learning a linear combineris performed according to one of the following criteria: minimum meansquare error, zero forcing, and maximum likelihood (ML).
 24. The methodof claim 22, wherein learning coefficients relating to self-FEXTcoupling into the victim line and the second sensor is performedaccording to a known sequence transmitted on one or more disturber linescausing the self-FEXT into the victim line.
 25. The method of claim 24,wherein learning coefficients relating to self-FEXT coupling into thevictim line and the second sensor is further performed using one or moreorthogonal sequences.
 26. The method of claim 22, wherein learningcoefficients relating to self-FEXT coupling into the victim line and thesecond sensor is performed during transmission of data mode symbols. 27.The method of claim 22, wherein receiving information relating to thevectored system comprises receiving information relating to externalnoise composed of one or more of: non-vectored very high-speed digitalsubscriber line (VDSL) FEXT, radio frequency interference (RFI), powerline communications (PLC), common mode noise, and impulse noise.
 28. Themethod of claim 22, wherein applying the learned linear combinercomprises mitigating external noise if the information received by thesecond sensor relates to the external noise.
 29. The method of claim 22,wherein applying the learned linear combiner comprises constructivelyfolding the far end transmitted signal from the second sensor into thevictim line if the information received by the second sensor relates tothe far end transmitted signal.
 30. The method of claim 22, whereinapplying the learned linear combiner comprises constructively foldingthe far end transmitted signal from the second sensor into the victimline and mitigating external noise if the information received by thesecond sensor relates to both the far end transmitted signal and theexternal noise.
 31. The method of claim 22, wherein the linear combineroperates according to one or two coefficients per tone.
 32. A customerpremises equipment (CPE) unit in a vectored system for improving asignal-to-noise ratio (SNR) of a far end transmitted signal on a victimline, comprising: a first sensor coupled to the victim line, the firstsensor configured to learn coefficients relating to self-induced far-endcrosstalk (self-FEXT) coupling into the first sensor and removeself-FEXT based on the learned coefficients; a second sensor configuredto receive information relating to a noise source comprising at leastone of: the vectored system, external noise, and the far end transmittedsignal on the victim line, the second sensor further configured to learncoefficients relating to self-FEXT coupling into the second sensor andremove self-FEXT based on the learned coefficients, and wherein thesecond sensor is configured to receive the information relating to thenoise source exclusive of any useful signals in the system; and a linearcombiner configured to undergo learning upon removal of self-FEXT fromthe first and the second sensor, wherein the linear combiner isconfigured to combine information relating to the victim line and thenoise source.
 33. The CPE of claim 32, wherein the second sensor isconfigured to operate according to a differential mode involving anothertwisted pair in the system or a common mode based on the victim line.34. The CPE of claim 32, wherein the linear combiner undergoes learningaccording to one of the following criteria: minimum mean square error,zero forcing, and maximum likelihood (ML).
 35. The CPE of claim 32,wherein the information received by the second sensor relating toexternal noise comprises of one or more of: non-vectored very high-speeddigital subscriber line (VDSL) FEXT, radio frequency interference (RFI),power line communications (PLC), common mode noise, and impulse noise.36. The CPE of claim 32, wherein the learned linear combiner mitigatesexternal noise if the information received by the second sensor relatesto the external noise.
 37. The CPE of claim 32, wherein the learnedlinear combiner constructively folds the far end transmitted signal fromthe second sensor into the victim line if the information received bythe second sensor relates to the far end transmitted signal.
 38. The CPEof claim 32, wherein the learned linear combiner constructively foldsthe far end transmitted signal from the second sensor into the victimline and mitigates external noise if the information received by thesecond sensor relates to both the far end transmitted signal and theexternal noise.
 39. The CPE of claim 32, wherein the linear combinercomprises one or two coefficients per tone.
 40. The method of claim 1,wherein the second sensor comprises a differential mode sensor coupledto an unused line in a same bundle as the victim line in the system. 41.The method of claim 1, wherein the second sensor comprises a common modesensor coupled between a twisted pair comprising the victim line andground.